Transformer-based super-resolution for AMSR-2 thermal satellite imagery using SwinIR + Real-ESRGAN. Achieves 2× native upsampling with cascaded 8× capability and physics-aware loss functions.
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Updated
Dec 3, 2025 - Python
Transformer-based super-resolution for AMSR-2 thermal satellite imagery using SwinIR + Real-ESRGAN. Achieves 2× native upsampling with cascaded 8× capability and physics-aware loss functions.
All image enhancement and restoration tools
Analysis resources for the Inter IIT Tech Meet 11.0 problem statement by ISRO: The Chandrayaan Moon Mapping Challenge
Production-grade Single Image Super-Resolution framework in pure PyTorch
ImageEditor is a PyQt5-based GUI application for advanced AI-powered image processing. It supports operations such as denoising, super-resolution, background removal, canvas resizing, and format conversion. It integrates powerful models such as SCUNet, SwinIR, and U²-Net.
A modular Image Restoration framework engineered with Design Patterns (Factory, Strategy, Registry). Unifying SOTA models like SwinIR, MambaIRv2, and CWFNet for Super-Resolution and Denoising.
SwinIR (Shifted windows Image Restoration) model for SISR (Single Image Super-Resolution) task using PyTorch
PyTorch implementation of our paper Road Sign Classification with Denoising Pipeline Approach
[ECCV] Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration. Advances in Image Manipulation (AIM) workshop ECCV 2022. Try it out! over 3.3M runs https://replicate.com/mv-lab/swin2sr
🌊 A Human-in-the-Loop workflow for creating HD images from text
Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
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